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Multi-step Amperometry

pypalmsens.MultiStepAmperometry


              flowchart TD
              pypalmsens.MultiStepAmperometry[MultiStepAmperometry]
              pypalmsens._methods.base.BaseTechnique[BaseTechnique]
              pypalmsens._methods.mixins.CurrentRangeMixin[CurrentRangeMixin]
              pypalmsens._methods.mixins.PretreatmentMixin[PretreatmentMixin]
              pypalmsens._methods.mixins.BiPotMixin[BiPotMixin]
              pypalmsens._methods.mixins.PostMeasurementMixin[PostMeasurementMixin]
              pypalmsens._methods.mixins.CurrentLimitsMixin[CurrentLimitsMixin]
              pypalmsens._methods.mixins.IrDropCompensationMixin[IrDropCompensationMixin]
              pypalmsens._methods.mixins.DataProcessingMixin[DataProcessingMixin]
              pypalmsens._methods.mixins.MultiplexerMixin[MultiplexerMixin]
              pypalmsens._methods.mixins.GeneralMixin[GeneralMixin]
              pypalmsens._methods.base_model.BaseModel[BaseModel]

                              pypalmsens._methods.base.BaseTechnique --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.base.BaseTechnique
                

                pypalmsens._methods.mixins.CurrentRangeMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.CurrentRangeMixin
                

                pypalmsens._methods.mixins.PretreatmentMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.PretreatmentMixin
                

                pypalmsens._methods.mixins.BiPotMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.BiPotMixin
                

                pypalmsens._methods.mixins.PostMeasurementMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.PostMeasurementMixin
                

                pypalmsens._methods.mixins.CurrentLimitsMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.CurrentLimitsMixin
                

                pypalmsens._methods.mixins.IrDropCompensationMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.IrDropCompensationMixin
                

                pypalmsens._methods.mixins.DataProcessingMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.DataProcessingMixin
                

                pypalmsens._methods.mixins.MultiplexerMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.MultiplexerMixin
                

                pypalmsens._methods.mixins.GeneralMixin --> pypalmsens.MultiStepAmperometry
                                pypalmsens._methods.base_model.BaseModel --> pypalmsens._methods.mixins.GeneralMixin
                



              click pypalmsens.MultiStepAmperometry href "" "pypalmsens.MultiStepAmperometry"
              click pypalmsens._methods.base.BaseTechnique href "" "pypalmsens._methods.base.BaseTechnique"
              click pypalmsens._methods.mixins.CurrentRangeMixin href "" "pypalmsens._methods.mixins.CurrentRangeMixin"
              click pypalmsens._methods.mixins.PretreatmentMixin href "" "pypalmsens._methods.mixins.PretreatmentMixin"
              click pypalmsens._methods.mixins.BiPotMixin href "" "pypalmsens._methods.mixins.BiPotMixin"
              click pypalmsens._methods.mixins.PostMeasurementMixin href "" "pypalmsens._methods.mixins.PostMeasurementMixin"
              click pypalmsens._methods.mixins.CurrentLimitsMixin href "" "pypalmsens._methods.mixins.CurrentLimitsMixin"
              click pypalmsens._methods.mixins.IrDropCompensationMixin href "" "pypalmsens._methods.mixins.IrDropCompensationMixin"
              click pypalmsens._methods.mixins.DataProcessingMixin href "" "pypalmsens._methods.mixins.DataProcessingMixin"
              click pypalmsens._methods.mixins.MultiplexerMixin href "" "pypalmsens._methods.mixins.MultiplexerMixin"
              click pypalmsens._methods.mixins.GeneralMixin href "" "pypalmsens._methods.mixins.GeneralMixin"
              click pypalmsens._methods.base_model.BaseModel href "" "pypalmsens._methods.base_model.BaseModel"
            

Create multi-step amperometry method parameters.

With Multistep amperometry you can specify the number of potential steps to apply and how long each step should last. Each step works exactly as a Chronoamperometry step. The current is continuously sampled with the specified interval time. A whole cycle of steps can be repeated several times.

Levels can be specified using pypalmsens.settings.ELevel.

Methods:

  • from_dict

    Structure technique instance from dict.

  • from_method_id

    Create new instance of appropriate technique from method ID.

  • to_dict

    Return the technique instance as a new key/value dictionary mapping.

Attributes:

bipot class-attribute instance-attribute

bipot: BiPot = Field(default_factory=BiPot)

Set the bipot settings.

current_limits class-attribute instance-attribute

current_limits: CurrentLimits = Field(default_factory=CurrentLimits)

Set the current limit settings.

current_range class-attribute instance-attribute

current_range: CurrentRange = Field(default_factory=CurrentRange)

Set the autoranging current.

data_processing class-attribute instance-attribute

data_processing: DataProcessing = Field(default_factory=DataProcessing)

Set the data processing settings.

enable_bipot_current class-attribute instance-attribute

enable_bipot_current: bool = False

Enable bipot current.

equilibration_time class-attribute instance-attribute

equilibration_time: float = 0.0

Equilibration time in s.

general class-attribute instance-attribute

general: General = Field(default_factory=General)

Sets general/other settings.

interval_time class-attribute instance-attribute

interval_time: float = 0.1

The time between two samples in s.

ir_drop_compensation class-attribute instance-attribute

ir_drop_compensation: IrDropCompensation = Field(default_factory=IrDropCompensation)

Set the iR drop compensation settings.

levels class-attribute instance-attribute

levels: list[ELevel] = Field(default_factory=lambda: [ELevel()])

The cto apply within a cycle.

Use ELevel() to create levels.

multiplexer class-attribute instance-attribute

multiplexer: Multiplexer = Field(default_factory=Multiplexer)

Set the multiplexer settings.

n_cycles class-attribute instance-attribute

n_cycles: int = 1

Number of repetitions.

post_measurement class-attribute instance-attribute

post_measurement: PostMeasurement = Field(default_factory=PostMeasurement)

Set the post measurement settings.

pretreatment class-attribute instance-attribute

pretreatment: Pretreatment = Field(default_factory=Pretreatment)

Set the pretreatment settings.

record_auxiliary_input class-attribute instance-attribute

record_auxiliary_input: bool = False

Record auxiliary input.

record_cell_potential class-attribute instance-attribute

record_cell_potential: bool = False

Record cell potential.

Counter electrode vs ground.

record_we_potential class-attribute instance-attribute

record_we_potential: bool = False

Record applied working electrode potential.

Reference electrode vs ground.

from_dict classmethod

from_dict(obj: dict[str, Any]) -> BaseTechnique

Structure technique instance from dict.

Opposite of .to_dict()

Source code in src/pypalmsens/_methods/base.py
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@classmethod
def from_dict(cls, obj: dict[str, Any]) -> BaseTechnique:
    """Structure technique instance from dict.

    Opposite of `.to_dict()`"""
    return cls.model_validate(obj)

from_method_id classmethod

from_method_id(id: str) -> BaseTechnique

Create new instance of appropriate technique from method ID.

Source code in src/pypalmsens/_methods/base.py
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@classmethod
def from_method_id(cls, id: str) -> BaseTechnique:
    """Create new instance of appropriate technique from method ID."""
    new = cls._registry[id]
    return new()

to_dict

to_dict() -> dict[str, Any]

Return the technique instance as a new key/value dictionary mapping.

Source code in src/pypalmsens/_methods/base.py
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def to_dict(self) -> dict[str, Any]:
    """Return the technique instance as a new key/value dictionary mapping."""
    return self.model_dump()